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CVE-2022-35973

Segfault in `QuantizedMatMul` in TensorFlow

Medium5.9EPSS 0.51%
Published
Updated
Reserved
Assigned by
GitHub_M

Description

TensorFlow is an open source platform for machine learning. If `QuantizedMatMul` is given nonscalar input for: `min_a`, `max_a`, `min_b`, or `max_b` It gives a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit aca766ac7693bf29ed0df55ad6bfcc78f35e7f48. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Scores

CVSS scores of CVE-2022-35973, by who scored it
Scored byCVSSScoreVector
GitHub_MCNA (assigner)3.1Medium5.9CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
NVDNVD · Modified3.1High7.5CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
EPSS (exploitation in 30 days)
0.51% · top 56% of all CVEs (6 Nov 2026)
CISA SSVC
Exploitation: none · Automatable: no · Technical impact: partial
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The list uses the assigner's score when there is one, then CISA's, then NVD's: Medium 5.9.

Weakness

Affected products

Affected packages

From reviewed advisories of the GitHub Advisory Database.

References (2)

Sources

The same CVE in the primary databases and aggregators, to check against.

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Record last updated .